This application relates to biometrics. More specifically, this application relates to methods and systems for using a various biometric sensor.
“Biometrics” refers generally to the statistical analysis of characteristics of living bodies. One category of biometrics includes “biometric identification,” which commonly operates under one of two modes to provide automatic identification of people or to verify purported identities of people. Biometric sensing technologies measure the physical features or behavioral characteristics of a person and compare those features to similar prerecorded measurements to determine whether there is a match. Physical features that are commonly used for biometric identification include faces, irises, hand geometry, vein structure, and fingerprint patterns, which is the most prevalent of all biometric-identification features. Current methods for analyzing collected fingerprints include optical, capacitive, radio-frequency, thermal, ultrasonic, and several other less common techniques.
Most existing fingerprint sensors rely on relatively high-quality contact between the finger and the sensor to obtain images. Obtaining adequate contact is both finicky and time-consuming because of factors related to individual characteristics of users of the sensors, the quality of the skin, and environmental variability. For some individuals and under some circumstances, achieving adequate contact is impossible. Ease of consistent fingerprint capture limits the effectiveness and scope of applications that utilize fingerprint biometrics for identity management. Furthermore, in some cultures and during specific public health events, there is a negative perception of contact-based fingerprinting. This was the case, for instance, during the SARS outbreak in 2003.
Contact measurement is a fundamental requirement for many forms of fingerprint acquisition, such as optical total internal reflectance, RF, capacitance, thermal, and ultrasound techniques. There have been a small number of fingerprint sensors that have been developed and marketed as “noncontact” fingerprint sensors. In many cases, these sensors use a pedestal or some other device to locate and stabilize the finger. Thus, although the fingerprint region is not in contact with the sensor, other portions of the finger are contacting the sensor, which compromises the advantages that a true noncontact fingerprint sensor would embody.
Most existing fingerprint sensors are also susceptible to being defeated through the use of artificial or altered fingerprint samples. Although each fingerprint technology may be susceptible to only specific types of artificial (or “spoof”) samples, the effort required to spoof most systems is fairly modest one the “trick” for doing so is known.